Project description:The paper describes a model of tumor invasion to bone marrow.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles
Kun-Wan Chen, Kenneth J Pienta
Theoretical Biology and Medical Modelling 2011, 8:36
Abstract:
Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact).
Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells.
Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models .
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide.
Please refer to CC0 Public Domain Dedication for more information.
Project description:The paper describes a model of tumor invasion to bone marrow.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles
Kun-Wan Chen, Kenneth J Pienta
Theoretical Biology and Medical Modelling 2011, 8:36
Abstract:
Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact).
Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells.
Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models .
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide.
Please refer to CC0 Public Domain Dedication for more information.
Project description:Breast tumor cells were found to remodel the bone marrow vascular microenviornment to support metastatic expansion. To identify tumor-derived factors that stimulate marrow endothelium, we studied the transcriptomes of four isogenic murine mammary tumor cell lines, 4T1.2, 4T1, 66cl4 and 67NR. To gain insight into the host vasculature in response to tumor colonization, we analysed the transcriptional signatures of EMCNhi/CD31hi endothelial cells extracted from heavily infiltrated bone marrow stroma (Metastatic) and from adjacent tumour-free bone marrow stroma (Non-metastatic), as well as from healthy bones (Control). This SuperSeries is composed of the SubSeries listed below.
Project description:Metastases of breast cancer is a prevalent problem with over 25% of patients suffering with metastatic disease. Of the patients that present with metastatic disease, the majority are estrogen receptor positive (ER+) and have skeletal metastases. These skeletal metastases can cause several issues including pathological fractures, chronic pain, and hypercalcemia. Currently, there are not any cures for metastatic breast cancer in bone and only therapies to mediate the osteolysis caused by breast cancer. The bone microenvironment presents various physical forces that can act on the tumor cell that has been studied in ER- cells, however, the physical forces on ER+ tumor cells have not been widely evaluated. In this study, we explored the transcriptional changes that occur at different matrix rigidities associated with the bone microenvironment (bone marrow: 0.5 kPa to 32 kPa; cortical and trabecular bone – 2 x 107 kPa). We observed that lower stiffnesses contributed to increased gene signatures associated with interleukin signaling. Additionally, we observed that downstream estrogen signaling outputs were modified. These interesting findings give us insights on what may be changing when ER+ tumor cells encounter rigidities associated with the bone microenvironment.
Project description:The molecular mechanisms underlying the development of bone metastases in breast cancer remain unclear. Disseminated tumour cells (DTCs) in the bone marrow of breast cancer patients are commonly identified, even in early stage disease, but their potential to initiate metastases is not known. The mechanism whereby DTCs become overt metastatic tumour cells (MTCs) is therefore, an area of considerable interest. This study explored the analysable yield of genetic material from human biopsy samples in order to describe differences in gene expression between DTCs and bone MTCs. Thirteen breast cancer patients with bone metastases underwent a CT-guided bone metastasis biopsy and a bone marrow biopsy. Tumour cells were enriched and gene expression profiling was conducted to identify differentially expressed genes. The analysable yield of sufficient RNA for microarray analysis was 60% from bone metastasis biopsies and 80% from bone marrow biopsies. A signature of 133 candidate genes differentially expressed between DTCs and MTCs was identified. Several genes relevant to breast cancer metastasis to bone (osteopontin, CTGF, parathyroid hormone receptor, EGFR) were significantly overexpressed in MTCs as compared to DTCs. Biopsies of bone metastases and bone marrow rarely yield enough tissue for robust molecular biology studies using clinical samples. The findings obtained however are interesting and seem to overlap with the bone metastasis gene expression signature described in murine xenograft models. Larger biopsy specimens or improved RNA extraction techniques may improve analysable yield and feasibility of these techniques. Gene expression profiling was utilized to compare DTCs obtained from bone marrow aspirates (A) to MTCs isolated from Computed Tomography (C) guided biopsies of bone metastases.